A robust image watermarking technique based on quantization noise visibility thresholds

Abstract

International audienceA tremendous amount of digital multimedia data is broadcasted daily over the internet. Since digital data can be very quickly and easily duplicated, intellectual property right protection techniques have become important and first appeared about fifty years ago (see [I.J. Cox, M.L. Miller, The First 50 Years of Electronic Watermarking, EURASIP J. Appl. Signal Process. 2 (2002) 126-132. [52]] for an extended review). Digital watermarking was born. Since its inception, many watermarking techniques have appeared, in all possible transformed spaces. However, an important lack in watermarking literature concerns the human visual system models. Several human visual system (HVS) model based watermarking techniques were designed in the late 1990's. Due to the weak robustness results, especially concerning geometrical distortions, the interest in such studies has reduced. In this paper, we intend to take advantage of recent advances in HVS models and watermarking techniques to revisit this issue. We will demonstrate that it is possible to resist too many attacks, including geometrical distortions, in HVS based watermarking algorithms. The perceptual model used here takes into account advanced features of the HVS identified from psychophysics experiments conducted in our laboratory. This model has been successfully applied in quality assessment and image coding schemes M. Carnec, P. Le Callet, D. Barba, An image quality assessment method based on perception of structural information, IEEE Internat. Conf. Image Process. 3 (2003) 185-188, N. Bekkat, A. Saadane, D. Barba, Masking effects in the quality assessment of coded images, in: SPIE Human Vision and Electronic Imaging V, 3959 (2000) 211-219. In this paper the human visual system model is used to create a perceptual mask in order to optimize the watermark strength. The optimal watermark obtained satisfies both invisibility and robustness requirements. Contrary to most watermarking schemes using advanced perceptual masks, in order to best thwart the de-synchronization problem induced by geometrical distortions, we propose here a Fourier domain embedding and detection technique optimizing the amplitude of the watermark. Finally, the robustness of the scheme obtained is assessed against all attacks provided by the Stirmark benchmark. This work proposes a new digital rights management technique using an advanced human visual system model that is able to resist various kind of attacks including many geometrical distortions

Error correcting codes for robust color wavelet watermarking

“…These characteristics include frequency sensitivity, that is the difference sensitivity of the human eye to sine wave gratings at different frequencies; luminance sensitivity, that is the different sensitivity of the eye to a noise signal on a constant background, depending on the average value of the background luminance and on the level of the noise luminance; and contrast masking, which refers to the perception of a signal in presence of a masking stimulus, and which depends on the relative spatial frequency, location and orientation. For example, an approach [30] based on the Fourier transform insists that interoperability between the HVS model and the watermark embedding may not be optimal and the DCT and DWT domains do not allow the implementation of a suitable HVS model. Another important observation is that the CSF is not adapted to predict invisibility for complex signals such as natural images, essentially because the HVS is modeled by a single channel.…”

“…The parameters used to demonstrate the performance of the Reed-Solomon codes are RS (40,11,30), RS (127, 9, 119), and RS (448, 8,441) and the code rates for these three cases are 0.275, 0.071, and 0.018 respectively. Therefore it is useless to use the high complexity Guruswami-Sudan algorithm as for the code rates are very low for the given cases and Sudan algorithm has similar performance, specially for RS (127, 9, 119) and RS (448, 8, 441), as seen in Figure 7.…”

Improved Content-Based Watermarking Using Scale-Invariant Feature Points

“…Another HVS Fourier domain mask is described in [9]. Here Florent et al introduce a perceptual model by taking into account advanced features of the HVS identified from psychophysics experiments.…”

Robust DWT based color image watermarking scheme

“…Human visual system (HVS) plays an important role in determining the kind of image processing that is done. Digital watermarking techniques also employ the characteristics of HVS to enhance the quality of watermarked images [3,4,5]. Various color models have been proposed for different electronic devices and print media.…”